Publication Date
5-2024
Date of Final Oral Examination (Defense)
12-11-2023
Type of Culminating Activity
Thesis
Degree Title
Master of Science in Mechanical Engineering
Department Filter
Mechanical and Biomechanical Engineering
Department
Mechanical and Biomedical Engineering
Supervisory Committee Chair
Gunes Uzer, Ph.D.
Supervisory Committee Member
Clare Fitzpatrick, Ph.D.
Supervisory Committee Member
Aykut Satici, Ph.D.
Abstract
Understanding the influence of mechanical forces on cell function and fate is crucial in unraveling the intricate mechanisms that govern cellular behavior. The cytoskeleton, a dynamic network of protein filaments, plays a pivotal role in sensing and transmitting mechanical cues within cells. The nucleus relies on cytoskeletal mechanical input through nuclear envelope adaptor proteins to sense external stimuli and respond by regulating intra-nuclear chromatin organization. This research provides a means for examining the interplay between mechanical forces and the cytoskeleton in regulating various cellular processes, including cell adhesion, migration, division, and differentiation. Through studying and simulating the cellular response to mechanical forces, this research aims to bridge the gap between mechanics and biology, uncovering the interrelation between physical forces and biochemical signaling. The developed computational framework reliably reconstructs nucleo-cytoskeletal morphology and computes cytoskeletal forces on the nuclear surface via finite element (FE) analyses. Utilizing this method, we found that cytoskeletal force was sensitive to changes in nuclear Young’s modulus and volume. Our cell specific models further confirm apical stress fibers’ role as critical load-carrying components, deforming the nuclei by 46.93% - 51.67% and matching target intact profiles with 2.19%-13.20% accuracy. In summary, our computational framework provides an important tool to probe nucleo-cytoskeletal Factin forces in cells and may shed light on fundamental questions in nuclear mechanotransduction and diseases where cytoskeletal force generation is impaired.
DOI
https://doi.org/10.18122/td.2168.boisestate
Recommended Citation
Goldfeldt, Madison Leigh, "A Computational Framework for Predicting Cell-Specific Nucleo-Cytoskeletal Forces" (2024). Boise State University Theses and Dissertations. 2168.
https://doi.org/10.18122/td.2168.boisestate
